Spatial Analysis of the Relationship Between Surface Temperature, Vegetation Cover, and Environmental Noise in the Ate District, Metropolitan Lima (2019–2024)

Urban environmental pressures are unevenly distributed across metropolitan landscapes, particularly in rapidly urbanizing districts where land-cover change, limited vegetation, and intense human activity interact. This study analyzes the spatial relationship between land surface temperature (LST), vegetation cover, and environmental noise in the district of Ate, Metropolitan Lima, Peru, during 2019–2024. The research integrates remote sensing, in situ acoustic monitoring, and spatial-statistical analysis to identify areas where thermal and acoustic stress overlap. LST and vegetation conditions are derived from Landsat 8 and 9 imagery processed in Google Earth Engine using thermal bands and the Normalized Difference Vegetation Index (NDVI). Environmental noise is characterized using georeferenced equivalent sound pressure levels (Leq) collected across residential, industrial, commercial, and open-space settings. All datasets are integrated in a geographic information system, where LST values are extracted around noise-monitoring locations using 100 m buffers. Statistical relationships are evaluated through normality testing, Pearson or Spearman correlation, and regression analysis. Spatial patterns are further examined using clustering techniques and Global Moran’s I to assess the concentration and spatial autocorrelation of areas with elevated LST and noise levels. By integrating thermal, vegetation, and acoustic indicators, the study seeks to identify urban environmental hotspots and assess the potential moderating role of vegetation. The findings are intended to support evidence-based urban planning, green-infrastructure strategies, and environmental management in heterogeneous and rapidly urbanizing areas of Metropolitan Lima.